BUA 400

Visual Analytics

This is the home page for BUA 345 - Visual Analytics

Instructor: Roy Thomas Meeting times: Mon/Wed 3:45pm to 5:05pm Room 301 Office Hours: Mon/Wed: 12:30pm to 2:00pm Tue/Thu: 1:00pm to 3:30pm

To run any of the materials locally on your own machine, you will need the following:

You can install all required R packages at once by running the following code in the R command line:

# first run this command:
install.packages(
  c(
    "broom", "cluster", "colorspace", "cowplot", "distill", "gapminder", 
    "GGally", "gganimate", "ggiraph", "ggdendro", "ggdist", "ggforce",
    "ggplot2movies", "ggrepel", "ggridges", "ggthemes", "gifski", "glue",
    "knitr", "learnr", "naniar", "margins", "MASS", "Matrix",
    "nycflights13", "palmerpenguins", "patchwork", "rgdal", "rmarkdown",
    "rnaturalearth", "sf", "shinyjs", "tidyverse", "transformr", "umap",
    "xaringan"
  )
)

# then run this command:
install.packages(
  "rnaturalearthhires", repos = "https://packages.ropensci.org", type = "source"
)

Reuse

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Any computer code (R, HTML, CSS, etc.) in slides and worksheets, including in slide and worksheet sources, is also licensed under MIT. Note that figures in slides may be pulled in from external sources and may be licensed under different terms. For such images, image credits are available in the slide notes, accessible via pressing the letter ‘p’.

Corrections

If you see mistakes or want to suggest changes, please create an issue on the source repository.